By the idea of combining the merits of reservoir computing (RC) of the Echo state network (ESN) and fuzzy inference system, a TSK fuzzy ESN for the black-box identification is proposed in this paper. The proposed network is constructed on the basis of the framework of ESN containing ...
1.TSK Fuzzy Systems Based on Fuzzy Partition and Support Vector Machines基于模糊划分和支持向量机的TSK模糊系统 2.This paper re-discusses TSK fuzzy systems modeling from a new perspective.从一个新角度重新探讨TSK模糊系统建模问题,引入并分析推导一种新的TSK模糊系统——CTSK。 3.Compared with the tradit...
Design of Adaptive TSK Fuzzy Self-Organizing Recurrent Cerebellar Model Articulation Controller for Chaotic Systems Control_2021 上传人:三月下雪天·上传时间:2025-02-26
IdentifyingRule-BasedTSKFuzzyModels ManfredMännle InstituteforComputerDesignandFaultTolerance UniversityofKarlsruhe D-76128Karlsruhe,Germany Phone:+49721608-6323,Fax:+49721608-3962 Email:maennle@computer ABSTRACT:Thisarticlepresentsarule-basedfuzzymodelfortheidentificationofnonlinearMISO(multipleinput, ...
A TSK fuzzy model with local linear friction models is suggested for real-time estimation of its consequent local parameters. The parameters update law is derived based on linear parameterization. In order to compensate for the effects resulting from estimation error and disturbance, a robust ...
Takagi-Sugeno-Kang (TSK) fuzzy systems are flexible and interpretable machine learning models; however, they may not be easily optimized when the data size is large, and/or the data dimensionality is high. This paper proposes a mini-batch gradient descent (MBGD) based algorithm to efficiently ...
Type 1 and Interval Type 2 Fuzzy Logic Systems in Python fuzzy-logicfuzzy-setssoft-computingfuzzy-logic-controlmamdanitskfuzzy-systems UpdatedJul 8, 2024 HTML nannib/NBTEMPOW Star8 Code Issues Pull requests NBTempoW V. 2.1 is a forensic tool for making timelines from block devices image files...
Each base building unit consists of an optimized zero-order TSK fuzzy classifier. For good interpretability of each base building unit, the antecedent parameters are solved by random selections of input features, random combinations of fuzzy rules, divisions of fuzzy partitions and generations of ...
This study proposes an adaptive Takagi-Sugeno-Kang-fuzzy (TSK-fuzzy) speed controller (ATFSC) for use in direct torque control (DTC) induction motor (IM) drives to improve their dynamic responses. The proposed controller consists of the TSK-fuzzy controller, which is used to approximate an ide...
Sine the weights of the output layer use a functional-type form in TFNN instead of a singleton-type form in fuzzy neural network (FNN), the TFNN provides more powerful representation than FNN. All the controller parameters of the proposed ATFNC system are tuned in the sense of Lyapunov ...